statilistes

Statilistes are researchers and practitioners who focus on statistical stability and cross-context comparability. The term describes a set of theories and methods aimed at understanding how statistical results hold up when data sources, measurement instruments, or timeframes change.

Origin and usage: The word is relatively new, appearing in scattered methodological discussions in the early 2010s. Because it has no fixed definition, different authors describe statilistes and their work in varying ways, often as part of meta-research, cross-study synthesis, or data harmonization.

Key concerns include measurement invariance, cross-temporal stability, and robustness to sampling variability and missing data. Statilistes develop procedures for harmonizing variables across datasets, assessing the portability of models, and designing studies that maximize comparability.

Applications: In social science, epidemiology, economics, and digital humanities, statiliste approaches inform replicability and evidence integration by guiding data collection, transformation, and interpretation across contexts.

Criticism and challenges: The term lacks formal consensus, and its boundaries overlap with existing fields such as psychometrics, robust statistics, and meta-analysis. Critics warn that the concept may become too broad or ill-defined without clear measurement criteria.

See also: measurement invariance, meta-analysis, data harmonization, robust statistics.